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Discovery of specialized NK cell populations infiltrating human melanoma metastases
Lucas Ferrari de Andrade, … , Guo-Cheng Yuan, Kai W. Wucherpfennig
Lucas Ferrari de Andrade, … , Guo-Cheng Yuan, Kai W. Wucherpfennig
Published December 5, 2019
Citation Information: JCI Insight. 2019;4(23):e133103. https://doi.org/10.1172/jci.insight.133103.
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Research Article Immunology Oncology

Discovery of specialized NK cell populations infiltrating human melanoma metastases

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Abstract

NK cells contribute to protective antitumor immunity, but little is known about the functional states of NK cells in human solid tumors. To address this issue, we performed single-cell RNA-seq analysis of NK cells isolated from human melanoma metastases, including lesions from patients who had progressed following checkpoint blockade. This analysis identified major differences in the transcriptional programs of tumor-infiltrating compared with circulating NK cells. Tumor-infiltrating NK cells represented 7 clusters with distinct gene expression programs indicative of significant functional specialization, including cytotoxicity and chemokine synthesis programs. In particular, NK cells from 3 clusters expressed high levels of XCL1 and XCL2, which encode 2 chemokines known to recruit XCR1+ cross-presenting DCs into tumors. In contrast, NK cells from 2 other clusters showed a higher level of expression of cytotoxicity genes. These data reveal key features of NK cells in human tumors and identify NK cell populations with specialized gene expression programs.

Authors

Lucas Ferrari de Andrade, Yuheng Lu, Adrienne Luoma, Yoshinaga Ito, Deng Pan, Jason W. Pyrdol, Charles H. Yoon, Guo-Cheng Yuan, Kai W. Wucherpfennig

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Figure 6

Validation of NK cell subpopulations by flow cytometry.

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Validation of NK cell subpopulations by flow cytometry.
(A) Expression o...
(A) Expression of genes used for identification of NK cell populations (FGFBP2 and FCGR3A) and effector molecules (GZMA and GZMK). The intensity of the blue color indicates the level of expression for selected genes in individual cells and is scaled separately between blood and tumor-infiltrating NK cells within the integrated data set from 5 patients. (B) Validation of 3 NK cell populations identified by scRNA-seq in blood samples by flow cytometry using FGFBP2 and CD16a as markers. NK cells were identified by gating on CD45+ and CD56+ cells that were negative for CD3ε, CD19, CD14, CD15, CD163, and a dead cell marker. A representative analysis is shown for patient CY165. (C) Quantification of 3 NK cell populations in blood and tumor samples based on FGFBP2 and CD16a markers. Labeling for granzymes A and K is also shown for each of the 3 populations. The genes named FCGR3A, FGFBP2, GZMA, and GZMK encode the proteins CD16a, FGFBP2, granzyme A, and granzyme K, respectively. Each dot represents an individual patient. MFI, mean fluorescence intensity. Statistical analysis was performed by 2-way ANOVA, Bonferroni’s post hoc tests; *P < 0.05, **P < 0.01, ***P < 0.001.

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